Detection Window Research Articles

Ex vivo detection of recreational consumed nitrous oxide in exhaled breath

The increasing use of recreational nitrous oxide (O) in the Netherlands and its link to traffic accidents highlights the need for reliable detection methods for law enforcement. This study focused on ex vivo detection of O in exhaled breath and examining its persistence in the human body. Firstly, a low-cost portable infrared based detector was selected and validated to detect O in air. Then, the influence of interferents and conditions potentially influencing the analysis were evaluated including relative humidity, ethanol, acetaldehyde and . Subsequently, O breathing dynamics were evaluated in vitro and ex vivo. Initially, a lung simulator was used to model respiratory mechanics and O decay, revealing detectable O levels up to 90 min after exposure. In the final part of this study, a controlled single and double dose of O gas was administered to 24 volunteers in an operating theatre. The presence of O in exhaled breath of the volunteers was analysed using infra red spectroscopy every 12-15 min. Our results show that O was detectable in exhaled breath for a minimum of 60 min post-administration and revealed a window of detection to potentially measure O for law enforcement and forensic purposes.

Evaluation of the applicability of urine lateral flow immunochromatography tests for the detection of cocaine in plasma samples

IntroductionQualitative analysis of cocaine in urine is a common practice in emergency settings. However, positive results from urine screening tests do not necessarily indicate recent exposure. In this context, plasma is considered a more appropriate option due to its shorter detection window and better correlation with symptomatology. Therefore, the availability of rapid tests for this biological matrix is extremely relevant in the clinical and emergency context. MethodsA lateral flow immunochromatography test designed for analyzing cocaine in urine was evaluated for use with plasma samples. A total of 412 samples from suspected cases of intoxication were processed and tested. Concurrently, the samples were analyzed for cocaine and its metabolites, benzoylecgonine and ecgonine methyl ester, using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Reliability parameters, including sensitivity, specificity, positive predictive value, negative predictive value, and efficiency, were calculated considering different cutoff values. ResultsApproximately 8.3 % of the samples tested positive in the immunoassay, while 10.2 % had a concentration greater than 5 ng/mL for at least one analyte in the LC-MS/MS analysis. Using benzoylecgonine as the target analyte with a cutoff of 40 ng/mL yielded the best reliability results, with 96.3 % sensitivity and 97.9 % specificity. Cocaine did not show satisfactory results, whereas ecgonine methyl ester, despite having 92.9 % sensitivity and 94.7 % specificity at its best cutoff (20 ng/mL), had a positive predictive value of only 38.2 %. ConclusionsThe study evaluated the suitability of using rapid urine tests for cocaine detection in plasma, offering a simple and quick drug screening method that is particularly useful in toxicological emergencies.

Drug detection in oral fluid and urine after single therapeutic doses of dexamphetamine, lisdexamphetamine, and methylphenidate in healthy volunteers.

Dexamphetamine, lisdexamphetamine, and methylphenidate are central stimulant drugs widely used to treat Attention-deficit/hyperactivity disorder (ADHD), but poor adherence may lead to treatment failure and the drugs are also subject to misuse and diversion. Drug analysis in oral fluid may thus be useful for monitoring adherence and misuse. We measured drug concentrations in oral fluid and urine after controlled dosing to investigate detection windows and evaluate the chosen cut-offs. Healthy volunteers ingested single oral doses of 10 mg dexamphetamine (n=11), 30 mg lisdexamphetamine (n=11), or 20 mg methylphenidate (n=10), after which they collected parallel oral fluid and urine samples every 8 hours for 4-6 days. Amphetamine (analytical cut-off, oral fluid: 1.5 ng/mL; urine: 50 ng/mL), methylphenidate (oral fluid: 0.06 ng/mL), and ritalinic acid (urine: 500 ng/mL) were analyzed using fully validated chromatographic methods. The median time from ingestion to the last detection in oral fluid was 67 ± 4.9 (lisdexamphetamine) and 69 ± 8.8 (dexamphetamine) hours for amphetamine and 36 ± 2.5 hours for methylphenidate. This was comparable to urine (77 ± 5.1 hours for lisdexamphetamine, 78 ± 4.5 hours for dexamphetamine, 41 ± 2.4 hours for ritalinic acid). The inter-individual variability in detection times was large, probably in part due to pH-dependent disposition. Using a logistic regression approach, we found similar detection rates as a function of time since intake in urine and oral fluid with the chosen cut-offs, with a high degree of probability for detection at least 24 hours after intake of a low therapeutic dose. This demonstrates the usefulness of oral fluid as a test matrix to assess adherence to ADHD medications, provided the analytical method is sensitive, requiring a cut-off as low as 0.1 ng/mL for methylphenidate. Detection windows similar to those in urine may be achieved for amphetamine and methylphenidate in oral fluid.

Assessing the Effects of Wheat Planting on Groundwater Under Climate Change: A Quantitative Adaptive Sliding Window Detection Strategy

Climate change has led to changes in precipitation patterns, exacerbating the overextraction of groundwater for wheat irrigation. Although many studies have examined the effects of wheat cultivation on groundwater storage (GWS), few studies have directly assessed the effects of wheat planting on GWS. We proposed a wheat subsiding effect detection (WSED) strategy using time-series remote sensing image to assess the effect of wheat area on GWS across China. The subsiding magnitude of the WSED is calculated as the GWS difference between the wheat area and adjacent nonwheat area in the self-adaptive moving window (the size and position of the sliding window can be automatically adjusted based on the characteristics of the data at the central pixel location). The effects of the wheat area on groundwater storage differ greatly among the change types of wheat area and planting regionalization, characterized by the strong subsiding effect in the wheat stable area, gain area, and Huanghuaihai zone (HWW, the most important wheat-producing region in China mainly includes the provinces and municipalities of Beijing, Tianjin, Henan, Hebei, Shandong, Anhui, and Jiangsu). Nearly 80% of the wheat area in the stable and gain regions had lower groundwater depth than nonwheat areas with significant differences (p < 0.05), resulting in a clear declining groundwater trend of approximately −1 cm/year. This study provides quantitative evidence for the effects of wheat planting on GWS regarding agricultural production and climate change adaptations.

Merging holography, fluorescence, and machine learning for in situ continuous characterization and classification of airborne microplastics

Abstract. The continued increase in global plastic production and poor waste management ensures that plastic pollution will be a serious environmental concern for years to come. Because of their size, shape, and relatively low density, plastic particles between 1 and 1000 µm in size (known as microplastics or MPs) emitted directly into the environment (“primary”) or created due to degradation (“secondary”) may be transported through the atmosphere, similarly to other coarse-mode particles such as mineral dust. MPs can thus be advected over great distances, reaching even the most pristine and remote areas of Earth, and may have significant negative consequences for humans and the environment. The detection and analysis of MPs once airborne, however, remains a challenge because most observational methods are offline and resource-intensive and, therefore, not capable of providing continuous quantitative information. In this study, we present results using an online in situ airflow cytometer (SwisensPoleno Jupiter; Swisens AG; Emmen, Switzerland) – coupled with machine learning – to detect, analyze, and classify airborne single-particle MPs in near real time. The performance of the instrument in differentiating between single-particle MPs of five common polymer types (including polypropylene, polyethylene, polyamide, poly(methyl methacrylate), and polyethylene terephthalate) was investigated under laboratory conditions using combined information about their size and shape (determined using holographic imaging) and fluorescence measured using three excitation wavelengths and five emission detection windows. The classification capability using these methods was determined alongside other coarse-mode aerosol particles with similar morphology or fluorescence characteristics, such as a mineral dust and several pollen taxa. The tested MPs exhibit a measurable fluorescence signal that not only allows them to be distinguished from other fluorescent particles, such as pollen, but also differentiated from each other, with high (> 90 %) classification accuracy based on their multispectral fluorescence signatures. The classification accuracies of machine learning models using only holographic images of particles, only the fluorescence response, and combined information from holography and fluorescence to predict particle types are presented and compared. The last model, using both the holographic images and fluorescence information for each particle, was the most optimal model used, providing the highest classification accuracy compared to employing models using only the holography or fluorescence response separately. The results provide a foundation for significantly improving the understanding of the properties and types of MPs present in the atmosphere.

Initial evaluation of 4-palmitoyloxy butyrate in whole blood as potential biomarker after γ-hydroxybutyric acid intake.

The problem of finding a suitable biomarker to widen the detection window of γ-hydroxybutyric acid (GHB) intake remains a challenge in forensic toxicology. Based on previously published results, the present study deals with the evaluation of a fatty acid ester of GHB (4-palmitoyloxy butyrate (GHB-Pal)) in whole blood as a potential biomarker to extend the detection window of GHB use e.g. in drug-facilitated sexual assaults (DFSA). A liquid chromatography-mass spectrometry (LC-MS/MS) method for the quantification of GHB-Pal in whole blood was validated. Whole blood samples were collected from subjects involed in police roadside controls (n=113) and from narcolepsy patients (n=10) after the controlled administration of Xyrem® (sodium oxybate). Both sample collectives were previously tested for GHB using two different methods: ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography-mass spectrometry (GC-MS). In samples from routine police casework, GHB-Pal was detected in 67 out of 113 analysed GHB-positive samples with a mean concentration of 0.8 ng/mL ± 0.5 ng/mL (standard deviation). Among samples that were tested positive for both compounds, no linear correlation was observed between GHB and GHB-Pal concentrations (r=0.508). In contrast, GHB-Pal was not detected in any of the blood samples analysed from the patients. The absence of GHB and GHB-Pal in the patient cohort may be attributed to the time interval between dose intake and blood collection (approx. 3 and 6 h), during which GHB was eliminated from the body. Furthermore, GHB-Pal was only detectable at a GHB concentration of at least 16 µg/mL, which indicates that endogenous concentrations or low GHB doses may not be sufficient for GHB-Pal formation. Due to missing correlation between both compounds and the lack of GHB-Pal detection several hours after GHB administration, it can be assumed that GHB-Pal in blood is not a suitable biomarker to widen the detection window of GHB.

Detection of Over 110 Anabolic-Androgenic Steroids, Corticosteroids and/or Their Esters in Horse Hair Using Ultra-High-Performance Liquid Chromatography-High-Resolution Mass Spectrometry and Gas Chromatography-Tandem Mass Spectrometry After Solid-Supported Liquid Extraction.

Anabolic-androgenic steroids (AAS) are banned substances in both human and equine sports. They are often administered intramuscularly to horses in esterified forms for the purpose of extending their duration of action. As such, the detection of intact esters of endogenous steroids in hair is particularly advantageous, as it can provide unequivocal proof of their external origin. Compared with urine and blood matrices, hair in general allows a longer detection window as long as the administered drug can be incorporated into hair and has not degraded. This can be useful in doping control of equine sports, where the timing of sample collection may be critical due to the transient nature of AAS in other biological fluids. This paper describes the detection of AAS and/or their esters, as well as corticosteroids, in horse hair using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS) and gas chromatography-tandem mass spectrometry (GC-MS/MS) after solid-supported liquid extraction (SLE) at basic pH. The developed UPLC-HRMS and GC-MS/MS methods in combination allowed the detection of 117 AAS, corticosteroids and/or their esters with estimated limits of detection down to sub-ppb levels and with good inter-day precision. Method applicability has been demonstrated through the detections of (i) boldenone undecylenate, nandrolone phenylpropionate and trenbolone acetate in three proficiency testing hair samples and (ii) nandrolone as a metabolite in a post-administration hair sample collected from a castrated horse having been administered nandrolone decanoate.

High Spatiotemporal Near-Infrared II Fluorescence Lifetime Imaging for Quantitative Detection of Clinical Tumor Margins.

Accurate detection of tumor margins is essential for successful cancer surgery. While indocyanine green (ICG)-based near-infrared (NIR) fluorescence (FL) surgical navigation enhances the visual identification of tumor margins, its accuracy remains subjective, underscoring the need for quantitative approaches. In this study, a high spatiotemporal fluorescence lifetime (FLT) imaging technology is developed in the second near-infrared window (NIR-II, 1000-1700nm) for quantitative tumor margin detection, utilizing folate receptor-targeted ICG nanoprobes (FPH-ICG). FPH-ICG exhibits a significantly prolonged NIR-II FLT (750 ±7ps vs 260 ±3ps) and increased NIR-II FL brightness (FPH-ICG/ICG=3.8). In vitro and in vivo studies confirm that FPH-ICG specifically targets folate receptor-α (FRα) on SK-OV-3 ovarian cancer cells, achieving high-contrast NIR-II FL imaging with a signal-to-background ratio of 10.8. Notably, NIR-II FLT imaging demonstrates superior accuracy (90%) and consistency in defining tumor margins compared to NIR-II FL imaging (58%) in both SK-OV-3 tumor-bearing mice and clinical tumor samples. These findings underscore the potential of NIR-II FLT imaging as a quantitative tool for guiding surgical tumor margin detection.

Advances in Global Remote Sensing Monitoring of Discolored Pine Trees Caused by Pine Wilt Disease: Platforms, Methods, and Future Directions

Pine wilt disease (PWD), caused by pine wood nematodes, is a major forest disease that poses a serious threat to global pine forest resources. Therefore, the prompt identification of PWD-discolored trees is crucial for controlling its spread. Currently, remote sensing is the primary approach for monitoring PWD. This study comprehensively reviews advances in the global remote sensing monitoring of PWD. It explores the remote sensing platforms and identification methods used in the detection of PWD-discolored trees, evaluates their precision, and provides prospects for existing problems. Three observations were made from existing studies: First, unmanned aerial vehicles (UAVs) are the dominant remote sensing platforms, and RGB data sources are the most commonly used for identifying PWD-discolored trees. Second, deep-learning methods are increasingly applied to identify PWD-discolored trees. Third, the early monitoring of PWD-discolored trees has gained increasing attention. This study reveals the problems associated with the acquisition of remote sensing images and identification algorithms. Future research directions include the fusion of multiple sensors to enhance the identification precision and early monitoring of PWD-discolored trees to obtain an optimal detection window period. This study aimed to provide technical references and scientific foundations for the comprehensive monitoring and control of PWD.

Detection and Identification of New Chlorphenesin Carbamate Metabolites in Human Urine and Metabolomic Characterization Using Liquid Chromatography-Q Exactive-HF-Orbitrap-Mass Spectrometry.

Chlorphenesin carbamate is a skeletal muscle relaxant, and one of its metabolites is 4-chlorophenoxyacetic acid (4-CPA), which is included on the Prohibited List of the World Anti-Doping Agency (WADA). The non-prohibited substance, chlorphenesin carbamate, as a potential source of 4-CPA, needs to be identified more strongly in doping control protocols. In this paper, the metabolism of chlorphenesin carbamate in human urine was studied. Ten volunteers were recruited to take chlorphenesin carbamate tablets orally, and urine samples were collected before and after being tested. The urine samples were detected by liquid chromatography-Q Exactive HF orbitrap mass spectrometry (LC-Q Exactive HF-MS) in full MS and full MS-ddMS2 scanning modes. Based on accurate molecular formulae determination and fragmentation pattern analysis by mass spectrometry, a total of 29 chlorphenesin carbamate metabolites were found, comprising 18 newly identified metabolites and 11 previously reported metabolites. There were five potential metabolic processes listed: hydroxylation, amide hydrolysis, C-oxidation, O-glucuronidation, sulfation, and their combinations. Chlorphenesin carbamate and the 29 metabolites were compared for their detection windows, and the findings indicated that the two recently reported metabolites, M9 and M10, had longer detection windows than the metabolites documented by the WADA. These metabolites are anticipated to be long-lasting biomarkers for the detection of chlorphenesin carbamate intake. By analyzing the results of metabolomic profiling, it was found that the metabolites with significant changes were mainly related to histidine metabolism and β-alanine metabolism pathways. This paper provides a comprehensive report on the metabolic profile of urinary chlorphenesin carbamate and reveals a point of view the changes in the metabolic in the human body, which is conducive to supporting the detection of chlorphenesin carbamate and meclofenoxate for doping control, as well as a better understanding of the mechanism of action of chlorphenesin carbamate as a drug.

Forensic metabolomics: Tracing cyanide-induced metabolic changes in fatalities.

Accurate detection of cyanide exposure is crucial, particularly in forensic science. However, cyanide's high volatility and potential biochemical conversions in biological samples pose challenges for direct detection, complicating the determination of cause of death. Identifying alternative cyanide metabolites as markers may mitigate false negatives and positives, extending the detection window in poisoning cases. This study aimed to evaluate metabolic changes induced by cyanide exposure in forensic cases using a multi-platform approach, including metabolomics and lipidomics analyses via liquid and gas chromatography coupled with high-resolution mass spectrometry. Results demonstrated clear discrimination between cyanide-exposed and control groups through OPLS-DA models. A total of 92 altered metabolites were identified in cyanide-exposed individuals compared to controls. Significant changes in metabolites primarily included glycerophospholipids (30.7 %), glycerolipids (14 %), fatty acyls (12.9 %), sphingolipids (8.0 %), amino acids and analogs (8.0 %), among others. Cyanide intoxication disrupted multiple metabolic pathways, including mitochondrial β-oxidation, acylcarnitine accumulation, a shift towards gluconeogenesis in amino acid metabolism, and ammonia homeostasis disturbance, affecting both ammonia recycling and the urea cycle. These pathways are essential for cellular energy production. The altered metabolic profiles provide insight into cyanide poisoning pathways, potentially aiding the development of new forensic diagnostic strategies. The area under the receiver operating characteristic curve was used to assess each model's predictive value. Findings suggest that metabolites such as phosphate and 3-hydroxybutyric acid could serve as diagnostic biomarkers in lethal cyanide poisoning cases. Future studies must evaluate these potential biomarkers' effectiveness in different fatal victim cohorts and validate the suggested panel through a targeted approach.

Evaluating the Impact of Phosphatidylethanol Testing on Hospital Outcomes.

Alcohol dependence remains a significant global health issue, exacerbated by the coronavirus disease 2019 (COVID-19) pandemic. Phosphatidylethanol (PEth), a direct biomarker of recent alcohol consumption, offers improved specificity, sensitivity, and a longer detection window of 2 - 4 weeks compared to traditional biomarkers. This study evaluates the association between PEth testing and hospital outcomes in hospitalized patients by comparing outcomes among patients with positive PEth and negative PEth test results. This retrospective cohort study used data from the TriNetX database, comprising de- identified medical records from 66 US healthcare organizations from 2015 to 2024. The study population included patients with documented PEth test results. Patients were divided into two groups: positive PEth test results (≥ 20 ng/mL) and negative PEth test results (≤ 19 ng/mL). Propensity score matching was performed to minimize bias, balancing for age, sex, race, ethnicity, and comorbidities such as cirrhosis, diabetes mellitus, hypertension, coronary artery disease, and chronic obstructive pulmonary disease (COPD). Key hospital outcomes assessed included mortality, delirium tremens, endoscopy/colonoscopy, liver transplant status, liver transplant rejection, liver transplant complications, hepatorenal syndrome, intensive care unit (ICU) admission, hepatic encephalopathy, and sarcopenia. These outcomes were chosen based on their prevalence in patients with alcohol use. Patients with positive PEth results demonstrated significantly worse outcomes compared to patients in the negative PEth group. Positive PEth results were associated with higher mortality (odds ratio, 10.037; P < 0.001), ICU admissions, and rates of complications such as hepatorenal syndrome, hepatic encephalopathy, and sarcopenia. Postoperative liver transplant complications and rejection were also more frequent in the positive cohort. This study highlights the association between recent alcohol use, as identified by PEth testing, and severe hospital outcomes. While PEth testing provides an objective measure of recent alcohol consumption, further research is needed to explore its role in improving clinical outcomes and guiding interventions for patients with alcohol use.

Use of Chemical Tracers in Sus scrofa Population Studies-A Scoping Review.

A highly invasive species, free-ranging Sus scrofa often negatively impact the ecosystem and are capable of spreading a number of impactful pathogens to domestic livestock. Measures taken to ameliorate these impacts and/or control population size are based on the delivery of oral baits containing bioactive chemicals or vaccines, e.g., classical swine fever vaccine. The efficacy of these methods depends on the rate at which inoculated baits are consumed by the pigs. Rhodamine B, tetracycline, and iophenoxic acid are commonly used to quantitate bait uptake in free-ranging pig population studies. All three are effective in this application but differ in fundamental characteristics. When used as a tracer, the effective dose of rhodamine B was established at 15 mg/kg to ensure a 12-week window of detection based on evaluation of hair samples using fluorescent microscopy. Tetracyclines are likewise effective tracers in free-ranging pigs, but the process of detection is highly invasive, i.e., requires euthanasia, and extraction of bone or teeth, followed by examination by fluorescence microscopy. Iophenoxic acid and its derivatives also highly suitable tracers and may be detected in serum for ≥9 months after exposure. Notably tracers used in free-ranging pigs are not suitable for behavioral studies in farm-raised pigs either because the detection method is highly invasive (tetracyclines) or because they are unapproved for use in meat destined for human consumption.

Toxicokinetic modelling of the synthetic cannabinoid 5F-MDMB-P7AICA and its main metabolite in pigs following pulmonary administration.

Since their emergence on the drug market, synthetic cannabinoids (SC) are still gaining increasing importance in forensic toxicology. The representatives of the so-called new psychoactive substances have in common that they have not undergone preclinical safety studies. Hence, knowledge on toxicokinetic (TK) data is sparse. As an alternative to human studies not being allowed for ethical reasons, a sophisticated pig model was applied in the present study to assess the TK of the SC 5F-MDMB-P7AICA. Pigs pulmonarily received 5F-MDMB-P7AICA via an ultrasonic nebulizer. The parent compound and its main metabolite 5F-MDMB-P7AICA dimethyl butanoic acid were determined in serum and whole blood using liquid chromatography-tandem mass spectrometry. Obtained data was analysed by population (pop) TK modelling. The final pop TK model parameters for pigs were upscaled via allometric scaling techniques for the prediction of human exposure. The serum concentration-time profiles of the parent and the pop TK analysis revealed that a 4-compartment model best describes the TK data. The administration of the aerosol into the lung compartment follows zero-order kinetics. A transit compartment was further included to accurately describe the time delay between detection of the parent and the metabolite. Despite the different structure, TK parameters were found to be comparable to other examined SC. The predictions of human SC exposure suggest that multiple administration of 5F-MDMB-P7AICA substantially enhances the window of detection. The simulations pose extrapolation of the data used for model development with respect to dose linearity and allometric scaling to humans.

Xylazine Pharmacokinetics in Patients Testing Positive for Fentanyl and Xylazine.

The increasing prevalence of xylazine in the illicit drug supply is a growing concern for major health consequences in individuals who use fentanyl mixed with xylazine, but limited data are available regarding the pharmacokinetics of xylazine in humans. Xylazine was quantified in serial remnant plasmas collected from 28 patients starting at the initial patient encounter and continuing for up to 52 h from presentation, using LC-MS/MS to calculate the terminal half-life for xylazine. Xylazine metabolites were identified by product ion scanning, and multiple reaction monitoring was used to estimate the relative abundance of xylazine metabolites in 74 collected plasma samples. The median terminal half-life for xylazine was calculated to be 12.0 h (range: 5.9-20.8). Oxo-xylazine and sulfone-xylazine metabolites were detected in all plasma specimens that contained xylazine. The half-life of xylazine in humans is longer than previously observed in animal studies, which furthers the current understanding of the expected duration of effects in individuals who use fentanyl mixed with xylazine and the window of detection. Both oxo-xylazine and sulfone-xylazine appear to circulate in plasma for as long as xylazine.

Optimization of a disposable pipette tips extraction (DPX) for the analysis of psychoactive substances in sweat specimens using Design of Experiments.

Novel psychoactive substances (NPS) continue to emerge in the marketplace and are often found as substances in traditional illicit drug materials, and users are often unaware of the presence of other drugs. The proper identification and confirmation of the exposure to a drug is made possible when a biological specimen is collected and tested. Sweat is an alternative biological matrix of great interest for clinical, and forensic analysis. One of the reasons is attributed to its expanded drug detection window, enabling a greater monitoring capacity, and provision of information on prospective drug use. However, the concentrations of drugs in sweat samples are often low, which requires highly sensitive and selective methods. Disposable pipette tips extraction (DPX) is a new miniaturized solid phase extraction technique capable of efficiently extracting analytes from biological specimens, providing high recoveries, and requiring minimized solvent use. This study describes the development and optimization of two methods for the extraction of basic and neutral psychoactive substances from sweat samples using GC-MS and Design of Experiments (DoE). The following extraction parameters were optimized by DoE techniques: sample volume, elution solvent volume, washing solvent volume, sample aspiration time, elution solvent aspiration time, and number of cycles performed, including the elution step. It was possible to design a simple extraction protocol that provided optimized recoveries for both basic and neutral compounds. The sum of analyte areas increased at a rate of 54.7% for compounds of basic character and 39.2% for compounds of neutral character. Therefore, our results were satisfactory, demonstrating that DPX can be successfully used for extracting the target drugs from sweat samples.

Improving the accuracy of soil organic matter mapping in typical Planosol areas based on prior knowledge and probability hybrid model

The use of remote sensing techniques for mapping soil organic matter (SOM) in black soil regions is well established. However, in areas where Planosols are interspersed with non-Planosols, tilling impacts the soil spectra of tilled soils at varying times and to different extents. As a result, errors may arise when modeling Planosols and non-Planosols collectively using conventional methods. This study developed a probability hybrid model specifically designed for the interlayered zones of Planosol and non-Planosol soils to accurately reflect the content and spatial distribution of SOM. A total of 712 topsoil samples were collected from the 852 Farm, a typical area with the interlayered zones of Planosol and non-Planosol soils in northeastern China. Cloud-free Sentinel-2 images were obtained during the bare soil period from April to May between 2021 and 2023. The spatial distribution of Planosol was detected, and the probability of soil classification was calculated using a random forest model. Based on soil classification probabilities, global models, multi-temporal ordinary hybrid models, and multi-temporal probability hybrid models were developed respectively. The results of SOM mapping using these different strategies were compared. Under seasonal reductive leaching, Planosol exhibits a distinct eluvial horizon beneath the topsoil. Long-term tilling leads to the mixing of this eluvial horizon with the topsoil in Planosol, resulting in spectral characteristics that differ significantly from those of other soil types. Accordingly, we propose a new remote sensing index—the Normalized Difference Planosol Index (NDPI), to reflect the upturning degree of the eluvial horizon and get “whiteness degree” information. We evaluated the effect of adding this index as an input on the detection of Planosol and the accuracy of SOM mapping. The results of the study show that (1) May is the optimal time window for SOM mapping and Planosol detection in the typical interlayered area of Planosol and non-Planosol soils. (2) Based on the random forest model combined with multi-period May bare soil images can accurately detect the spatial distribution of Planosol with the highest accuracy, the overall accuracy is 97.66 %; (3) The hybrid models outperform the global model, with the probability hybrid model achieving the highest accuracy (R2=0.8056, RMSE=4.2869 g/kg) and the mapping is more continuous and smoother. (4) The inclusion of NDPI improves the accuracy of Planosol spatial distribution detection and SOM mapping in Planosol areas, resulting in an increase in the Kappa coefficient by 0.0168 and an improvement in R2 by 0.0122. The present study innovatively utilizes remote sensing imagery to monitor Planosol, thus expanding the application of remote sensing technology in digital soil mapping.

Determining the optimal time window to detect emerald ash borer damage for effective management.

The emerald ash borer (EAB) is an invasive pest of global concern. Accurate detection of EAB is crucial for effective management. Traditional field surveys fail to meet large-scale monitoring requirements. Remote sensing methods offer a potential solution, but the phenological decline of ash trees may obscure the remote sensing features for detecting EAB. Therefore, determining the timing of leaf abscission caused by EAB before phenology is crucial for effective detection. We collected time-series data of Leaf Area Index (LAI), leaf sizes, and hyperspectral images of damaged ash trees throughout the growing season to determine the optimal detecting time window for EAB detection using field surveys or remote sensing techniques. Significant differences in LAI and leaf size were observed throughout the growing season among ash trees with different EAB infestation degrees, providing a basis for small-scale field surveys. However, in May and June, the hyperspectral reflectance showed no variation. The difference began to appear in July and became apparent from August to October. By October, severely EAB-infested ash trees had almost completely defoliated. Machine learning classification results showed that accuracies after July were higher than before July. After July, the highest classification accuracy reached 100%, while the highest accuracy before July was only 88.57%. Selecting the optimal monitoring time significantly enhanced detection accuracy. The optimal period for field surveys is from May to November, whereas for remote sensing it is from August to October. Identifying the optimal months enables us to achieve more efficient decision-making and management. © 2024 Society of Chemical Industry.

Improved object detection network for pipeline leakage localization in the pneumatic system based on thermal images

The infrared thermal imaging method can effectively identify and locate leakage sites using the temperature characteristics of pneumatic system leakage. However, it is limited by the tiny dimensions of the objects, color shifts of varying background temperatures, and indistinctness of feature details. To address these issues, we integrate Omni-Dimensional Dynamic Convolution (ODDC), Squeeze-and-Excitation (SE) attention module, and Normalized Gaussian Wasserstein Distance (NWD) with You Only Look Once (YOLO) into a framework, named ODSW-YOLO, for the precise localization of leakage. Specifically, ODDC is employed to adjust the kernel parameters for improving the accuracy of detecting small targets. To reduce the influence of varying background temperatures, SE attention is adopted to extract key features. NWD is used to enhance the feature details by checking the small feature changes within the detection window. Finally, extensive experiments show that ODSW-YOLO improves the detection accuracy from 0.677 to 0.755, which surpasses the baseline model (YOLOv5).

Modeling the effect of superconductor properties on sensitivity and responsivity of superconducting nanowire single photon detector

Superconducting nanowire single photon detector (SNSPD) is a leading candidate for applications requiring the fundamental limit of light detection at high detection rates. While SNSPD technology employing nanowires from conventional low temperature superconducting detectors is mature with several commercial solutions, other material options with higher transition temperature approaching liquid nitrogen with faster signal responses are actively being explored. In this context, we develop a comprehensive model that predicts the final potential response from an SNSPD incorporating several physical and material aspects. A phase diagram of photon detection is developed that describes the latching phases and the photon sensitivity as a function of biasing current and temperature for both low temperature and high temperature superconductors. On the one hand, while low temperature superconductors are observed to be more sensitive than high temperature superconductors (HTSs) under any given biasing condition, a biasing window for a single photon detection with HTS nanowires is identified. On the other hand, HTS nanowires demonstrate three orders of magnitude faster response times than the low temperature superconductor nanowire at the same biasing condition, making it uniquely suited for several practical applications.